MACBETH: Development of a Training Game for the Mitigation of Cognitive Bias

MACBETH: Development of a Training Game for the Mitigation of Cognitive Bias

Norah E. Dunbar (Department of Communication, Center for Applied Social Research, University of Oklahoma, Norman, OK, USA), Scott N. Wilson (University of Oklahoma, Norman, OK, USA), Bradley J. Adame (University of Oklahoma, Norman, OK, USA), Javier Elizondo (University of Oklahoma, Norman, OK, USA), Matthew L. Jensen (University of Oklahoma, Norman, OK, USA), Claude H. Miller (University of Oklahoma, Norman, OK, USA), Abigail Allums Kauffman (University of Texas Permian Basin, Odessa, TX, USA), Toby Seltsam (University of Oklahoma, Norman, OK, USA), Elena Bessarabova (University of Oklahoma, Norman, OK, USA), Cindy Vincent (University of Oklahoma, Norman, OK, USA), Sara K. Straub (University of Oklahoma, Norman, OK, USA), Ryan Ralston (University of Oklahoma, Norman, OK, USA), Christopher L. Dulawan (University of Arizona, Tucson, AZ, USA), Dennis Ramirez (University of Wisconsin Madison, Madison, WI, USA), Kurt Squire (University of Wisconsin Madison, Madison, WI, USA), Joseph S. Valacich (University of Arizona, Tucson, AZ, USA) and Judee K. Burgoon (University of Arizona, Tucson, AZ, USA)
Copyright: © 2013 |Pages: 20
DOI: 10.4018/ijgbl.2013100102
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Abstract

This paper describes the process of rapid iterative prototyping used by a research team developing a training video game for the Sirius program funded by the Intelligence Advanced Research Projects Activity (IARPA). Described are three stages of development, including a paper prototype, and builds for alpha and beta testing. Game development is documented, and the process of playtesting is reviewed with a focus on the challenges and lessons-learned. Advances made in the development of the game through the playtesting process are discussed along with implications of the rapid iterative prototyping approach.
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Theoretical Approach To Cognitively Biased Information Processing

A primary causal mechanism cited for biased information processing and poor credibility assessment is the reliance on heuristic social information processing—a nonanalytic orientation in which only a minimal set of informational cues are considered as long as processing accuracy is deemed sufficient. As defined by Chaiken’s Heuristic-Systematic Model of information processing (HSM; Chaiken, 1980; Todorov, Chaiken, & Henderson, 2002), heuristics are mental shortcuts, or simple decision rules, arising from conventional beliefs and expectations used repeatedly in daily interactions. In contrast to heuristic processing, systematic information processing requires more careful consideration of all available evidence, and is thus much more cognitively taxing (Chen & Chaiken, 1999).

The HSM posits that reliance on heuristics is often preferable because it minimizes cognitive effort while satisfying motivational concerns with sufficient reliability. Heuristics often provide swift solutions to complex, ill-structured problems (Silverman, 1992; Van Boven & Loewenstein, 2005), however, reliance on heuristics can also lead to insufficient consideration and/or disregard of relevant, diagnostic information. Consequently, although heuristics do not always lead to bias, an overreliance on them can result in decreased soundness of credibility assessments. According to the HSM, motivation, time, and ability to process information are critical elements for reducing analytical reliance on heuristic processing, and encouraging more optimal systematic, deliberative processing.

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